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        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

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        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        Report generated on 2024-03-24, 15:12 EDT based on data in: /work/gmgi/Fisheries/epiage/haddock/QC/trimmed_fastqc


        General Statistics

        Showing 272/272 rows and 5/7 columns.
        Sample Name% BP Trimmed% Dups% GCMedian Read LengthM Seqs
        Mae-263_S1_R1_001
        23.8%
        Mae-263_S1_R1_001_val_1
        32.6%
        31%
        107bp
        169.7M
        Mae-263_S1_R2_001
        23.2%
        Mae-263_S1_R2_001_val_2
        31.7%
        31%
        107bp
        169.7M
        Mae-266_S2_R1_001
        23.9%
        Mae-266_S2_R1_001_val_1
        29.9%
        30%
        102bp
        178.5M
        Mae-266_S2_R2_001
        23.3%
        Mae-266_S2_R2_001_val_2
        29.1%
        31%
        107bp
        178.5M
        Mae-274_S3_R1_001
        20.5%
        Mae-274_S3_R1_001_val_1
        39.9%
        30%
        117bp
        140.7M
        Mae-274_S3_R2_001
        20.4%
        Mae-274_S3_R2_001_val_2
        39.4%
        30%
        117bp
        140.7M
        Mae-278_S4_R1_001
        22.6%
        Mae-278_S4_R1_001_val_1
        35.9%
        30%
        107bp
        140.1M
        Mae-278_S4_R2_001
        22.5%
        Mae-278_S4_R2_001_val_2
        35.8%
        30%
        107bp
        140.1M
        Mae-281_S5_R1_001
        24.6%
        Mae-281_S5_R1_001_val_1
        39.5%
        31%
        102bp
        179.9M
        Mae-281_S5_R2_001
        24.5%
        Mae-281_S5_R2_001_val_2
        39.0%
        31%
        102bp
        179.9M
        Mae-285_S6_R1_001
        24.6%
        Mae-285_S6_R1_001_val_1
        41.6%
        30%
        102bp
        146.3M
        Mae-285_S6_R2_001
        24.4%
        Mae-285_S6_R2_001_val_2
        41.0%
        31%
        102bp
        146.3M
        Mae-293_S7_R1_001
        22.5%
        Mae-293_S7_R1_001_val_1
        37.1%
        29%
        107bp
        159.5M
        Mae-293_S7_R2_001
        22.3%
        Mae-293_S7_R2_001_val_2
        36.8%
        30%
        112bp
        159.5M
        Mae-294_S8_R1_001
        15.1%
        Mae-294_S8_R1_001_val_1
        44.6%
        29%
        127bp
        189.2M
        Mae-294_S8_R2_001
        15.0%
        Mae-294_S8_R2_001_val_2
        43.5%
        29%
        127bp
        189.2M
        Mae-295_S9_R1_001
        23.2%
        Mae-295_S9_R1_001_val_1
        36.5%
        30%
        107bp
        115.7M
        Mae-295_S9_R2_001
        22.9%
        Mae-295_S9_R2_001_val_2
        36.0%
        30%
        107bp
        115.7M
        Mae-298_S10_R1_001
        24.2%
        Mae-298_S10_R1_001_val_1
        35.7%
        31%
        102bp
        152.8M
        Mae-298_S10_R2_001
        24.0%
        Mae-298_S10_R2_001_val_2
        35.2%
        31%
        102bp
        152.8M
        Mae-302_S11_R1_001
        21.0%
        Mae-302_S11_R1_001_val_1
        43.7%
        30%
        112bp
        115.7M
        Mae-302_S11_R2_001
        21.0%
        Mae-302_S11_R2_001_val_2
        42.5%
        30%
        112bp
        115.7M
        Mae-305_S12_R1_001
        23.2%
        Mae-305_S12_R1_001_val_1
        42.2%
        30%
        107bp
        143.1M
        Mae-305_S12_R2_001
        23.2%
        Mae-305_S12_R2_001_val_2
        41.4%
        31%
        107bp
        143.1M
        Mae-310_S13_R1_001
        23.4%
        Mae-310_S13_R1_001_val_1
        35.5%
        30%
        107bp
        177.2M
        Mae-310_S13_R2_001
        23.4%
        Mae-310_S13_R2_001_val_2
        35.0%
        30%
        107bp
        177.2M
        Mae-311_S14_R1_001
        20.1%
        Mae-311_S14_R1_001_val_1
        37.5%
        29%
        117bp
        188.9M
        Mae-311_S14_R2_001
        20.0%
        Mae-311_S14_R2_001_val_2
        37.2%
        30%
        117bp
        188.9M
        Mae-317_S15_R1_001
        17.8%
        Mae-317_S15_R1_001_val_1
        40.2%
        29%
        127bp
        146.2M
        Mae-317_S15_R2_001
        17.8%
        Mae-317_S15_R2_001_val_2
        39.6%
        29%
        127bp
        146.2M
        Mae-322_S16_R1_001
        23.4%
        Mae-322_S16_R1_001_val_1
        32.2%
        30%
        107bp
        186.9M
        Mae-322_S16_R2_001
        23.2%
        Mae-322_S16_R2_001_val_2
        30.9%
        31%
        107bp
        186.9M
        Mae-327_S17_R1_001
        20.6%
        Mae-327_S17_R1_001_val_1
        37.7%
        29%
        112bp
        98.8M
        Mae-327_S17_R2_001
        20.5%
        Mae-327_S17_R2_001_val_2
        37.0%
        29%
        117bp
        98.8M
        Mae-329_S18_R1_001
        20.5%
        Mae-329_S18_R1_001_val_1
        37.7%
        29%
        112bp
        141.2M
        Mae-329_S18_R2_001
        20.4%
        Mae-329_S18_R2_001_val_2
        37.2%
        30%
        112bp
        141.2M
        Mae-330_S19_R1_001
        24.2%
        Mae-330_S19_R1_001_val_1
        36.1%
        30%
        102bp
        215.5M
        Mae-330_S19_R2_001
        23.9%
        Mae-330_S19_R2_001_val_2
        35.4%
        31%
        107bp
        215.5M
        Mae-338_S20_R1_001
        19.8%
        Mae-338_S20_R1_001_val_1
        35.9%
        30%
        117bp
        186.7M
        Mae-338_S20_R2_001
        19.5%
        Mae-338_S20_R2_001_val_2
        35.0%
        30%
        117bp
        186.7M
        Mae-342_S21_R1_001
        20.3%
        Mae-342_S21_R1_001_val_1
        41.4%
        29%
        117bp
        227.4M
        Mae-342_S21_R2_001
        20.1%
        Mae-342_S21_R2_001_val_2
        40.5%
        29%
        122bp
        227.4M
        Mae-343_S22_R1_001
        24.0%
        Mae-343_S22_R1_001_val_1
        31.5%
        30%
        107bp
        218.5M
        Mae-343_S22_R2_001
        23.9%
        Mae-343_S22_R2_001_val_2
        31.2%
        30%
        107bp
        218.5M
        Mae-344_S23_R1_001
        23.9%
        Mae-344_S23_R1_001_val_1
        37.1%
        31%
        107bp
        213.5M
        Mae-344_S23_R2_001
        23.5%
        Mae-344_S23_R2_001_val_2
        36.4%
        31%
        107bp
        213.5M
        Mae-350_S24_R1_001
        23.2%
        Mae-350_S24_R1_001_val_1
        41.1%
        32%
        107bp
        164.9M
        Mae-350_S24_R2_001
        23.1%
        Mae-350_S24_R2_001_val_2
        40.4%
        33%
        107bp
        164.9M
        Mae-352_S25_R1_001
        25.8%
        Mae-352_S25_R1_001_val_1
        31.0%
        31%
        97bp
        128.2M
        Mae-352_S25_R2_001
        25.4%
        Mae-352_S25_R2_001_val_2
        30.2%
        32%
        97bp
        128.2M
        Mae-356_S26_R1_001
        24.9%
        Mae-356_S26_R1_001_val_1
        31.6%
        31%
        102bp
        140.8M
        Mae-356_S26_R2_001
        24.5%
        Mae-356_S26_R2_001_val_2
        31.3%
        31%
        102bp
        140.8M
        Mae-368_S27_R1_001
        24.2%
        Mae-368_S27_R1_001_val_1
        31.7%
        30%
        102bp
        132.4M
        Mae-368_S27_R2_001
        23.9%
        Mae-368_S27_R2_001_val_2
        31.3%
        31%
        102bp
        132.4M
        Mae-371_S28_R1_001
        22.6%
        Mae-371_S28_R1_001_val_1
        32.2%
        30%
        107bp
        113.6M
        Mae-371_S28_R2_001
        22.5%
        Mae-371_S28_R2_001_val_2
        31.7%
        30%
        112bp
        113.6M
        Mae-378_S29_R1_001
        19.9%
        Mae-378_S29_R1_001_val_1
        36.4%
        29%
        117bp
        101.7M
        Mae-378_S29_R2_001
        19.7%
        Mae-378_S29_R2_001_val_2
        35.8%
        29%
        122bp
        101.7M
        Mae-390_S32_R1_001
        22.7%
        Mae-390_S32_R1_001_val_1
        39.9%
        30%
        107bp
        217.5M
        Mae-390_S32_R2_001
        22.6%
        Mae-390_S32_R2_001_val_2
        39.3%
        30%
        107bp
        217.5M
        Mae-396_S33_R1_001
        22.7%
        Mae-396_S33_R1_001_val_1
        30.6%
        30%
        107bp
        112.0M
        Mae-396_S33_R2_001
        22.4%
        Mae-396_S33_R2_001_val_2
        30.2%
        30%
        107bp
        112.0M
        Mae-399_S34_R1_001
        25.1%
        Mae-399_S34_R1_001_val_1
        28.4%
        30%
        102bp
        126.0M
        Mae-399_S34_R2_001
        24.9%
        Mae-399_S34_R2_001_val_2
        28.0%
        30%
        102bp
        126.0M
        Mae-403_S35_R1_001
        22.6%
        Mae-403_S35_R1_001_val_1
        31.5%
        30%
        107bp
        116.3M
        Mae-403_S35_R2_001
        22.3%
        Mae-403_S35_R2_001_val_2
        31.1%
        30%
        107bp
        116.3M
        Mae-405_S36_R1_001
        22.8%
        Mae-405_S36_R1_001_val_1
        27.6%
        30%
        107bp
        91.8M
        Mae-405_S36_R2_001
        22.5%
        Mae-405_S36_R2_001_val_2
        27.4%
        30%
        107bp
        91.8M
        Mae-410_S37_R1_001
        20.9%
        Mae-410_S37_R1_001_val_1
        36.0%
        29%
        112bp
        125.6M
        Mae-410_S37_R2_001
        20.7%
        Mae-410_S37_R2_001_val_2
        35.4%
        29%
        117bp
        125.6M
        Mae-414_S38_R1_001
        24.6%
        Mae-414_S38_R1_001_val_1
        31.3%
        31%
        102bp
        106.5M
        Mae-414_S38_R2_001
        24.2%
        Mae-414_S38_R2_001_val_2
        30.7%
        31%
        102bp
        106.5M
        Mae-421_S39_R1_001
        27.0%
        Mae-421_S39_R1_001_val_1
        31.9%
        31%
        92bp
        126.8M
        Mae-421_S39_R2_001
        26.7%
        Mae-421_S39_R2_001_val_2
        31.3%
        31%
        97bp
        126.8M
        Mae-422_S40_R1_001
        24.5%
        Mae-422_S40_R1_001_val_1
        29.3%
        30%
        102bp
        96.2M
        Mae-422_S40_R2_001
        23.8%
        Mae-422_S40_R2_001_val_2
        28.7%
        30%
        102bp
        96.2M
        Mae-424_S41_R1_001
        28.6%
        Mae-424_S41_R1_001_val_1
        28.9%
        32%
        92bp
        103.7M
        Mae-424_S41_R2_001
        28.4%
        Mae-424_S41_R2_001_val_2
        28.5%
        32%
        92bp
        103.7M
        Mae-428_S42_R1_001
        21.3%
        Mae-428_S42_R1_001_val_1
        35.0%
        30%
        112bp
        114.6M
        Mae-428_S42_R2_001
        20.9%
        Mae-428_S42_R2_001_val_2
        34.3%
        30%
        112bp
        114.6M
        Mae-432_S43_R1_001
        23.6%
        Mae-432_S43_R1_001_val_1
        30.0%
        30%
        102bp
        122.9M
        Mae-432_S43_R2_001
        23.3%
        Mae-432_S43_R2_001_val_2
        29.6%
        31%
        107bp
        122.9M
        Mae-436_S44_R1_001
        21.4%
        Mae-436_S44_R1_001_val_1
        27.4%
        31%
        112bp
        128.5M
        Mae-436_S44_R2_001
        21.1%
        Mae-436_S44_R2_001_val_2
        27.1%
        31%
        112bp
        128.5M
        Mae-440_S45_R1_001
        24.0%
        Mae-440_S45_R1_001_val_1
        32.6%
        31%
        102bp
        115.7M
        Mae-440_S45_R2_001
        23.5%
        Mae-440_S45_R2_001_val_2
        32.0%
        31%
        107bp
        115.7M
        Mae-441_S46_R1_001
        24.6%
        Mae-441_S46_R1_001_val_1
        30.3%
        31%
        102bp
        116.3M
        Mae-441_S46_R2_001
        24.4%
        Mae-441_S46_R2_001_val_2
        29.8%
        31%
        102bp
        116.3M
        Mae-449_S48_R1_001
        21.7%
        Mae-449_S48_R1_001_val_1
        32.2%
        30%
        112bp
        186.4M
        Mae-449_S48_R2_001
        21.3%
        Mae-449_S48_R2_001_val_2
        31.1%
        31%
        112bp
        186.4M
        Mae-454_S49_R1_001
        24.2%
        Mae-454_S49_R1_001_val_1
        27.9%
        30%
        102bp
        89.9M
        Mae-454_S49_R2_001
        24.0%
        Mae-454_S49_R2_001_val_2
        27.5%
        30%
        102bp
        89.9M
        Mae-464_S50_R1_001
        18.2%
        Mae-464_S50_R1_001_val_1
        43.7%
        29%
        122bp
        99.5M
        Mae-464_S50_R2_001
        18.0%
        Mae-464_S50_R2_001_val_2
        42.9%
        29%
        127bp
        99.5M
        Mae-468_S51_R1_001
        22.9%
        Mae-468_S51_R1_001_val_1
        36.6%
        30%
        107bp
        160.6M
        Mae-468_S51_R2_001
        22.7%
        Mae-468_S51_R2_001_val_2
        35.8%
        30%
        107bp
        160.6M
        Mae-470_S52_R1_001
        20.1%
        Mae-470_S52_R1_001_val_1
        37.5%
        29%
        117bp
        114.4M
        Mae-470_S52_R2_001
        19.9%
        Mae-470_S52_R2_001_val_2
        36.8%
        29%
        117bp
        114.4M
        Mae-474_S57_R1_001
        24.7%
        Mae-474_S57_R1_001_val_1
        33.4%
        31%
        102bp
        176.7M
        Mae-474_S57_R2_001
        24.3%
        Mae-474_S57_R2_001_val_2
        32.7%
        31%
        102bp
        176.7M
        Mae-475_S53_R1_001
        22.8%
        Mae-475_S53_R1_001_val_1
        30.8%
        30%
        107bp
        129.0M
        Mae-475_S53_R2_001
        22.6%
        Mae-475_S53_R2_001_val_2
        30.4%
        30%
        107bp
        129.0M
        Mae-477_S54_R1_001
        23.8%
        Mae-477_S54_R1_001_val_1
        34.4%
        30%
        102bp
        157.9M
        Mae-477_S54_R2_001
        23.6%
        Mae-477_S54_R2_001_val_2
        34.0%
        30%
        107bp
        157.9M
        Mae-481_S55_R1_001
        22.9%
        Mae-481_S55_R1_001_val_1
        34.0%
        30%
        107bp
        189.3M
        Mae-481_S55_R2_001
        22.6%
        Mae-481_S55_R2_001_val_2
        33.7%
        30%
        107bp
        189.3M
        Mae-488_S56_R1_001
        24.3%
        Mae-488_S56_R1_001_val_1
        29.5%
        30%
        102bp
        140.4M
        Mae-488_S56_R2_001
        24.1%
        Mae-488_S56_R2_001_val_2
        29.2%
        30%
        102bp
        140.4M
        Mae-495_S47_R1_001
        18.9%
        Mae-495_S47_R1_001_val_1
        46.0%
        29%
        122bp
        139.4M
        Mae-495_S47_R2_001
        18.7%
        Mae-495_S47_R2_001_val_2
        44.9%
        29%
        122bp
        139.4M
        Mae-496_S58_R1_001
        14.5%
        Mae-496_S58_R1_001_val_1
        41.3%
        29%
        127bp
        138.9M
        Mae-496_S58_R2_001
        14.4%
        Mae-496_S58_R2_001_val_2
        39.8%
        29%
        127bp
        138.9M
        Mae-499_S59_R1_001
        23.3%
        Mae-499_S59_R1_001_val_1
        38.4%
        30%
        107bp
        185.6M
        Mae-499_S59_R2_001
        23.2%
        Mae-499_S59_R2_001_val_2
        37.8%
        30%
        107bp
        185.6M
        Mae-501_S60_R1_001
        23.5%
        Mae-501_S60_R1_001_val_1
        36.4%
        30%
        107bp
        209.5M
        Mae-501_S60_R2_001
        23.4%
        Mae-501_S60_R2_001_val_2
        35.9%
        30%
        107bp
        209.5M
        Mae-502_S61_R1_001
        24.8%
        Mae-502_S61_R1_001_val_1
        35.0%
        30%
        102bp
        165.5M
        Mae-502_S61_R2_001
        24.6%
        Mae-502_S61_R2_001_val_2
        34.8%
        30%
        102bp
        165.5M
        Mae-509_S62_R1_001
        23.6%
        Mae-509_S62_R1_001_val_1
        34.2%
        30%
        107bp
        200.3M
        Mae-509_S62_R2_001
        23.4%
        Mae-509_S62_R2_001_val_2
        33.7%
        30%
        107bp
        200.3M
        Mae-512_S63_R1_001
        24.0%
        Mae-512_S63_R1_001_val_1
        34.7%
        30%
        102bp
        198.9M
        Mae-512_S63_R2_001
        23.6%
        Mae-512_S63_R2_001_val_2
        34.0%
        31%
        107bp
        198.9M
        Mae-519_S64_R1_001
        24.6%
        Mae-519_S64_R1_001_val_1
        34.3%
        30%
        102bp
        142.7M
        Mae-519_S64_R2_001
        24.4%
        Mae-519_S64_R2_001_val_2
        34.0%
        31%
        102bp
        142.7M
        Mae-520_S65_R1_001
        24.5%
        Mae-520_S65_R1_001_val_1
        35.5%
        30%
        102bp
        149.4M
        Mae-520_S65_R2_001
        24.4%
        Mae-520_S65_R2_001_val_2
        34.9%
        30%
        102bp
        149.4M
        Mae-524_S66_R1_001
        21.2%
        Mae-524_S66_R1_001_val_1
        38.7%
        29%
        112bp
        161.7M
        Mae-524_S66_R2_001
        20.9%
        Mae-524_S66_R2_001_val_2
        37.9%
        30%
        112bp
        161.7M
        Mae-525_S67_R1_001
        23.0%
        Mae-525_S67_R1_001_val_1
        31.3%
        30%
        107bp
        198.1M
        Mae-525_S67_R2_001
        22.6%
        Mae-525_S67_R2_001_val_2
        30.6%
        30%
        107bp
        198.1M
        Mae-533_S68_R1_001
        24.7%
        Mae-533_S68_R1_001_val_1
        35.3%
        30%
        102bp
        225.1M
        Mae-533_S68_R2_001
        24.5%
        Mae-533_S68_R2_001_val_2
        34.8%
        31%
        102bp
        225.1M
        Mae-535_S69_R1_001
        22.3%
        Mae-535_S69_R1_001_val_1
        34.9%
        30%
        107bp
        211.2M
        Mae-535_S69_R2_001
        22.1%
        Mae-535_S69_R2_001_val_2
        34.2%
        31%
        107bp
        211.2M
        Mae-537_S70_R1_001
        22.1%
        Mae-537_S70_R1_001_val_1
        31.4%
        30%
        107bp
        243.9M
        Mae-537_S70_R2_001
        21.8%
        Mae-537_S70_R2_001_val_2
        30.6%
        30%
        112bp
        243.9M

        Cutadapt

        Version: 1.18

        Cutadapt is a tool to find and remove adapter sequences, primers, poly-A tails and other types of unwanted sequence from your high-throughput sequencing reads.DOI: 10.14806/ej.17.1.200.

        Filtered Reads

        This plot shows the number of reads (SE) / pairs (PE) removed by Cutadapt.

        Created with MultiQC

        Trimmed Sequence Lengths (3')

        This plot shows the number of reads with certain lengths of adapter trimmed for the 3' end.

        Obs/Exp shows the raw counts divided by the number expected due to sequencing errors. A defined peak may be related to adapter length.

        See the cutadapt documentation for more information on how these numbers are generated.

        Created with MultiQC

        FastQC

        Version: 0.11.9

        FastQC is a quality control tool for high throughput sequence data, written by Simon Andrews at the Babraham Institute in Cambridge.

        Sequence Counts

        Sequence counts for each sample. Duplicate read counts are an estimate only.

        This plot show the total number of reads, broken down into unique and duplicate if possible (only more recent versions of FastQC give duplicate info).

        You can read more about duplicate calculation in the FastQC documentation. A small part has been copied here for convenience:

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        Created with MultiQC

        Sequence Quality Histograms

        The mean quality value across each base position in the read.

        To enable multiple samples to be plotted on the same graph, only the mean quality scores are plotted (unlike the box plots seen in FastQC reports).

        Taken from the FastQC help:

        The y-axis on the graph shows the quality scores. The higher the score, the better the base call. The background of the graph divides the y axis into very good quality calls (green), calls of reasonable quality (orange), and calls of poor quality (red). The quality of calls on most platforms will degrade as the run progresses, so it is common to see base calls falling into the orange area towards the end of a read.

        Created with MultiQC

        Per Sequence Quality Scores

        The number of reads with average quality scores. Shows if a subset of reads has poor quality.

        From the FastQC help:

        The per sequence quality score report allows you to see if a subset of your sequences have universally low quality values. It is often the case that a subset of sequences will have universally poor quality, however these should represent only a small percentage of the total sequences.

        Created with MultiQC

        Per Base Sequence Content

        The proportion of each base position for which each of the four normal DNA bases has been called.

        To enable multiple samples to be shown in a single plot, the base composition data is shown as a heatmap. The colours represent the balance between the four bases: an even distribution should give an even muddy brown colour. Hover over the plot to see the percentage of the four bases under the cursor.

        To see the data as a line plot, as in the original FastQC graph, click on a sample track.

        From the FastQC help:

        Per Base Sequence Content plots out the proportion of each base position in a file for which each of the four normal DNA bases has been called.

        In a random library you would expect that there would be little to no difference between the different bases of a sequence run, so the lines in this plot should run parallel with each other. The relative amount of each base should reflect the overall amount of these bases in your genome, but in any case they should not be hugely imbalanced from each other.

        It's worth noting that some types of library will always produce biased sequence composition, normally at the start of the read. Libraries produced by priming using random hexamers (including nearly all RNA-Seq libraries) and those which were fragmented using transposases inherit an intrinsic bias in the positions at which reads start. This bias does not concern an absolute sequence, but instead provides enrichement of a number of different K-mers at the 5' end of the reads. Whilst this is a true technical bias, it isn't something which can be corrected by trimming and in most cases doesn't seem to adversely affect the downstream analysis.

        Click a sample row to see a line plot for that dataset.
        Rollover for sample name
        Position: -
        %T: -
        %C: -
        %A: -
        %G: -

        Per Sequence GC Content

        The average GC content of reads. Normal random library typically have a roughly normal distribution of GC content.

        From the FastQC help:

        This module measures the GC content across the whole length of each sequence in a file and compares it to a modelled normal distribution of GC content.

        In a normal random library you would expect to see a roughly normal distribution of GC content where the central peak corresponds to the overall GC content of the underlying genome. Since we don't know the the GC content of the genome the modal GC content is calculated from the observed data and used to build a reference distribution.

        An unusually shaped distribution could indicate a contaminated library or some other kinds of biased subset. A normal distribution which is shifted indicates some systematic bias which is independent of base position. If there is a systematic bias which creates a shifted normal distribution then this won't be flagged as an error by the module since it doesn't know what your genome's GC content should be.

        Created with MultiQC

        Per Base N Content

        The percentage of base calls at each position for which an N was called.

        From the FastQC help:

        If a sequencer is unable to make a base call with sufficient confidence then it will normally substitute an N rather than a conventional base call. This graph shows the percentage of base calls at each position for which an N was called.

        It's not unusual to see a very low proportion of Ns appearing in a sequence, especially nearer the end of a sequence. However, if this proportion rises above a few percent it suggests that the analysis pipeline was unable to interpret the data well enough to make valid base calls.

        Created with MultiQC

        Sequence Length Distribution

        The distribution of fragment sizes (read lengths) found. See the FastQC help

        Created with MultiQC

        Sequence Duplication Levels

        The relative level of duplication found for every sequence.

        From the FastQC Help:

        In a diverse library most sequences will occur only once in the final set. A low level of duplication may indicate a very high level of coverage of the target sequence, but a high level of duplication is more likely to indicate some kind of enrichment bias (eg PCR over amplification). This graph shows the degree of duplication for every sequence in a library: the relative number of sequences with different degrees of duplication.

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        In a properly diverse library most sequences should fall into the far left of the plot in both the red and blue lines. A general level of enrichment, indicating broad oversequencing in the library will tend to flatten the lines, lowering the low end and generally raising other categories. More specific enrichments of subsets, or the presence of low complexity contaminants will tend to produce spikes towards the right of the plot.

        Created with MultiQC

        Overrepresented sequences by sample

        The total amount of overrepresented sequences found in each library.

        FastQC calculates and lists overrepresented sequences in FastQ files. It would not be possible to show this for all samples in a MultiQC report, so instead this plot shows the number of sequences categorized as overrepresented.

        Sometimes, a single sequence may account for a large number of reads in a dataset. To show this, the bars are split into two: the first shows the overrepresented reads that come from the single most common sequence. The second shows the total count from all remaining overrepresented sequences.

        From the FastQC Help:

        A normal high-throughput library will contain a diverse set of sequences, with no individual sequence making up a tiny fraction of the whole. Finding that a single sequence is very overrepresented in the set either means that it is highly biologically significant, or indicates that the library is contaminated, or not as diverse as you expected.

        FastQC lists all the sequences which make up more than 0.1% of the total. To conserve memory only sequences which appear in the first 100,000 sequences are tracked to the end of the file. It is therefore possible that a sequence which is overrepresented but doesn't appear at the start of the file for some reason could be missed by this module.

        Created with MultiQC

        Top overrepresented sequences

        Top overrepresented sequences across all samples. The table shows 20 most overrepresented sequences across all samples, ranked by the number of samples they occur in.

        Showing 7/7 rows and 3/3 columns.
        Overrepresented sequenceSamplesOccurrences% of all reads
        GTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGT
        136
        150213152
        0.7188%
        CACACACACACACACACACACACACACACACACACACACACACACACACA
        136
        97464466
        0.4664%
        ACACACACACACACACACACACACACACACACACACACACACACACACAC
        136
        86628141
        0.4145%
        TGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTG
        136
        92598164
        0.4431%
        TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT
        135
        51648760
        0.2472%
        AGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAG
        1
        189403
        0.0009%
        GAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGAGA
        1
        165876
        0.0008%

        Adapter Content

        The cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position.

        Note that only samples with ≥ 0.1% adapter contamination are shown.

        There may be several lines per sample, as one is shown for each adapter detected in the file.

        From the FastQC Help:

        The plot shows a cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position. Once a sequence has been seen in a read it is counted as being present right through to the end of the read so the percentages you see will only increase as the read length goes on.

        No samples found with any adapter contamination > 0.1%

        Status Checks

        Status for each FastQC section showing whether results seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

        FastQC assigns a status for each section of the report. These give a quick evaluation of whether the results of the analysis seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

        It is important to stress that although the analysis results appear to give a pass/fail result, these evaluations must be taken in the context of what you expect from your library. A 'normal' sample as far as FastQC is concerned is random and diverse. Some experiments may be expected to produce libraries which are biased in particular ways. You should treat the summary evaluations therefore as pointers to where you should concentrate your attention and understand why your library may not look random and diverse.

        Specific guidance on how to interpret the output of each module can be found in the relevant report section, or in the FastQC help.

        In this heatmap, we summarise all of these into a single heatmap for a quick overview. Note that not all FastQC sections have plots in MultiQC reports, but all status checks are shown in this heatmap.

        Created with MultiQC

        Software Versions

        Software Versions lists versions of software tools extracted from file contents.

        SoftwareVersion
        Cutadapt1.18
        FastQC0.11.9